Typically, mines designed to be utilized in coastal regions are smaller in size compared to mines designed to be utilized in deep ocean depths. Therefore, when mining these coastal regions a larger number of smaller mines need to be deployed. One of the challenges encountered during littoral mine countermeasures (MCM) is distinguishing seafloor clutters from mines present in coastal regions. These seafloor clutters, which can range from man-made debris to rock outcrops, can also appear as having mine-like characteristics when viewed by sonar imagery. Accordingly, the ability to accurately distinguish between actual mines and seafloor clutter in sonar imagery is of utmost importance.
One known method of detecting underwater objects in coastal regions is by installing sensors capable of operating at multiple narrowband frequencies on a variety of unmanned underwater vehicles (UUVs). An example of a UUV having a multiple narrow band frequency sensor is a seafloor crawler including an IMAGENEX 881A rotating head sonar. Crawling vehicles operate in close proximity to the seafloor; therefore, objects imaged by the sensor produce no acoustic shadow. Additionally, the use of low-resolution imagery results in images of objects being poorly defined or having no shape. It is often the shape and size of the object and acoustic shadow that yield some of the most salient features used by classifiers in determining whether the detected underwater object is a target or clutter. Not having produced a defined shape or acoustic shadow causes detected underwater objects to appear as bright spots on a screen. Referring to FIG. 1, the detected objects appear as bright spots on a screen with little discernable shape. As a result, it is not possible to accurately determine the class (target or non-target) of the underwater object.
There exists a need for a method and system that is capable of accurately classifying the objects detected by low-resolution sonar systems which is relatively inexpensive and easy to deploy.